c#版的smooth weighted round-robin balancing

Nginx基于权重的轮询算法的实现，它不但实现了基于权重的轮询算法，而且还实现了平滑的算法。
所谓平滑，就是在一段时间内，不仅服务器被选择的次数的分布和它们的权重一致，而且调度算法还比较均匀的选择服务器，而不会集中一段时间之内只选择某一个权重比较高的服务器。
如果使用随机算法选择或者普通的基于权重的轮询算法，就比较容易造成某个服务集中被调用压力过大。

举个例子，比如权重为{a:5, b:1, c:1)的一组服务器，Nginx的平滑的轮询算法选择的序列为{ a, a, b, a, c, a, a },
这显然要比{ c, b, a, a, a, a, a }序列更平滑，更合理，不会造成对a服务器的集中访问。

c#版本代码如下：

/// <summary>
  2     /// 权重对象
  3     /// </summary>
  4     public class WeightObject
  5     {
  6         /// <summary>
  7         /// 当前权重
  8         /// </summary>
  9         public int CurrentWeight  { set; get; }
 10 
 11         /// <summary>
 12         /// 有效
 13         /// </summary>
 14         public int EffectiveWeight { set; get; }
 15 
 16 
 17         /// <summary>
 18         /// 权重
 19         /// </summary>
 20         public int Weight { set; get; }
 21 
 22 
 23     }
 24 
 25     public class BalancingAssignHelper
 26     {
 27 
 28         /// <summary>
 29         /// 算法：
 30         /// on each peer selection we increase current_weight of each eligible peer by its weight, 
 31         ///select peer with greatest current_weight and reduce its current_weight by total number of weight points distribute damong peers.
 32         public static T Next<T>(List<T> servers) where T : WeightObject
 33         {
 34             if (servers == null || servers.Count == 0)
 35             {
 36                 return null;
 37             }
 38             if (servers.Count == 1)
 39             {
 40                 return servers[0];
 41             }
 42 
 43             T best = null;
 44 
 45             //计算权重总和
 46             int total = 0;
 47             for (int i = 0; i < servers.Count; i++)
 48             {
 49 
 50                 T w = servers[i];
 51 
 52                 if (w == null)
 53                 {
 54                     continue;
 55                 }
 56 
 57                 w.CurrentWeight += w.EffectiveWeight;
 58                 total += w.EffectiveWeight;
 59 
 60                 if (w.EffectiveWeight < w.Weight)
 61                 {
 62                     w.EffectiveWeight++;
 63                 }
 64 
 65                 if (best == null || w.CurrentWeight > best.CurrentWeight)
 66                 {
 67                     best = w;
 68                 }
 69 
 70             }
 71 
 72             if (best == null)
 73             {
 74                 return null;
 75             }
 76 
 77             best.CurrentWeight -= total;
 78             return best;
 79         }
 80     }
 81 
 82     //1.声明一个继承RandomObject的实体类，如：*
 83     public class ServerWeightObject : WeightObject
 84 {
 85     /// <summary>
 86     /// 名称
 87     /// </summary>
 88     public string Name { set; get; }
 89     /// <summary>
 90     /// 描述
 91     /// </summary>
 92     public string Description { set; get; }
 93     //...其它相关的字段/属性
 94 
 95     public ServerWeightObject()
 96     {
 97         EffectiveWeight = Weight;
 98     }
 99 }
100 
101 
102     /// <summary>
103     /// DEMO
104     /// </summary>
105     public class BalancingAssignDemo
106     {
107 
108         public void Main()
109         {
110 
111             //1.初始化调用数据，如：
112             List<ServerWeightObject> list = new List<ServerWeightObject>();
113             list.Add(new ServerWeightObject { Name = "A", Weight = 2 });
114             list.Add(new ServerWeightObject { Name = "B", Weight = 3 });
115             list.Add(new ServerWeightObject { Name = "C", Weight = 5});
116             //list.Add(new ServerWeightObject { Name = "D", Weight = 3 });
117             //list.Add(new ServerWeightObject { Name = "E", Weight = 4 });
118             //list.Add(new ServerWeightObject { Name = "F", Weight = 5 });
119             //list.Add(new ServerWeightObject { Name = "G", Weight = 60 });
120             for (int i = 0; i < 20; i++)
121             {
122                 System.Diagnostics.Debug.Write(BalancingAssignHelper.Next<ServerWeightObject>(list).Name);
123             }
124         }
125     }